For Forty Years He Said the Standard Cholesterol Target Was Wrong. A Computer Finally Agreed.

Allan Sniderman has spent the better part of four decades at McGill telling anyone who would sit still that the cholesterol number most American doctors chase is the wrong one. He said it in journals, at podiums, and in a 2021 paper he titled, with the subtlety of a man who was tired of arguing, “The Debate Is Over.” This spring his name turned up on a study in JAMA that ran his thesis through a computer and handed him the verdict he had been waiting for. The test he champions, it concluded, would prevent more heart attacks and strokes than the one on your last lab report, at a price the healthcare system should be willing to pay.

It is also a simulation, not a trial, and the gap between those two words matters more than the wave of July headlines telling millions of Americans they are getting the wrong cholesterol test would suggest. It matters for a second reason too. Read past the apoB headline and the same model quietly hands a win to a number that is already sitting on your lab report, costing nothing.

Here is what the paper actually did. A Northwestern team led by Ciaran Kohli-Lynch built a model of 250,000 hypothetical adults, all eligible for a statin, none with existing heart disease, assembled from the records of 4,149 real people in the federal NHANES survey. They ran three strategies at these imaginary patients over their imaginary lifetimes: chase an LDL cholesterol below 100, chase a non-HDL cholesterol below 118, or chase apolipoprotein B below 78.7. The computer tallied the heart attacks, the strokes, the years of life, and the bills.

The apoB strategy won. Against a non-HDL target it bought each additional quality-adjusted year of life for about $30,300, comfortably under the $120,000-per-year line the authors set for good value, and it came out optimal in 65 percent of the probabilistic runs. Fine. The more damning number sits one rung down. Non-HDL cholesterol, a figure already printed on every standard lipid panel and costing nothing extra to read, beat the LDL target outright. It saved money, roughly $2.1 million across the modeled population, while adding 965 quality-adjusted life-years. The cheapest upgrade in the study was the one nobody has to buy.

So the pitch in the press cycle is pay for a fancier test. The result in the table is that the standard LDL target finished dead last of the three, and the free number already on your bloodwork beat it.

The biology is not mystical. LDL cholesterol measures the amount of cholesterol riding inside a class of particles. ApoB counts the particles themselves, one molecule per atherogenic particle, which is the thing that actually burrows into an artery wall. For most people the two numbers track and the distinction is academic. For the growing share of Americans carrying high triglycerides, insulin resistance, and metabolic syndrome, they come apart: the LDL number reads reassuringly normal while the particle count runs high, and the patient gets waved through. European practice recognized years ago that apoB, or the free non-HDL number that approximates it, catches risk more reliably in exactly those metabolic patients, where LDL and particle count diverge. American practice keeps anchoring to LDL anyway, on inertia and habit and the comfort of a test everyone already knows how to bill.

On the merits, then, the skeptics of the standard panel have a case, and this publication is not in the business of defending guideline inertia. But it is worth being precise about what the study is. It is a cost-effectiveness model. It did not enroll a single person. It did not measure a single heart attack. It assumed the drugs work, assumed how aggressively each strategy would push treatment, and let the math follow those assumptions to their conclusion. No randomized trial has ever taken two groups of real patients, managed one by apoB and one by LDL, and counted who ended up in the cardiac unit. The model prevented heart attacks. It did not treat a patient.

That is not a knock on Kohli-Lynch, whose work was funded by an American Heart Association career award and who was careful, in the paper, to call his question what it was: is it worth the extra money to switch. It is a caution about the machinery that turns a modeling paper from April into a July press cycle telling patients their doctor is running the wrong test. The paper supports a narrower and more useful claim, that apoB is a cost-effective way to guide treatment and that the free non-HDL number is rarely treated as the primary target in American practice and probably should be. It does not support the certainty of the headline.

And the byline deserves a plain word. A model built to test whether apoB is worth the cost returned a yes, and among its authors is the man who has argued for apoB longer and louder than anyone alive. That does not make the result wrong. Sniderman’s evidence has been piling up for decades and most of it points his way. It does mean the vindication arrived in the one venue that can be tuned to a prior, and that has never felt a heart attack. Forty years of argument, and the answer came from a simulation. Sniderman will take it. The trial that would actually settle it has still not been run.

Sources

1. JAMA – Luebbe, Sniderman, Moran, Wilkins, Kohli-Lynch, “Cost-Effectiveness of ApoB, Non–HDL-C, and LDL-C Goals for Primary Prevention Lipid-Lowering Therapy” (2026)
2. Northwestern Feinberg – “Little-Used Cholesterol Test Could Prevent More Heart Attacks, Strokes” (press release, 2026)
3. ScienceDaily – “Millions may be getting the wrong cholesterol test” (2026)
4. PubMed – Sniderman et al., “Apolipoprotein B… The Debate Is Over” (JAMA Cardiology, 2021)
5. European Heart Journal – discordance among apoB, non-HDL-C, and triglycerides in cardiovascular prevention (2024)